Thesis etd-04062018-112655 |
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Thesis type
Tesi di dottorato di ricerca
Author
CONDELLO, VINCENZO
URN
etd-04062018-112655
Thesis title
Analysis of gene and microRNA expression profiles in Follicular Variant of Papillary Thyroid Carcinomas with and without distant metastases
Academic discipline
MED/05
Course of study
FISIOPATOLOGIA CLINICA
Supervisors
tutor Prof. Basolo, Fulvio
Keywords
- FVPTC; Distant Metastasis; Gene Expression
- miRNA Expression
Graduation session start date
20/04/2018
Availability
Withheld
Release date
20/04/2088
Summary
Introduction: Follicular variant (FV) is one of the most frequent subsets of papillary thyroid carcinoma (PTC), accounting for 15 to 30% of all PTC cases. Usually FVPTC is associated with a good outcome. Nevertheless, in rare cases, it can have distant metastases (1-9%).
Aim: Firstly, the primary goal of this study was to investigate the gene and miRNA expression profiles in two groups of homogeneous FVPTCs that were distinguished only by the presence of distant metastasis. The ultimate goal, however, would be to include these expression profiles in a larger project and use them as useful tools to detect precociously those carcinomas with extremely aggressiveness and metastatic behavior.
Methods/Case Presentation: Twelve primary FVPTCs with distant metastasis and 12 non-metastatic FVPTCs with similar clinicopathological features were selected. All tumors were analyzed with the nanoString nCounter system for gene and miRNA expression using two distinct panels, composed of 740 genes, involved in cancer progression, and 798 miRNAs, respectively. Expression data were analyzed using the nanoString nSolver 3.0 software, and an unsupervised hierarchical clustering analysis was performed. In addition, we performed the analysis to evaluate the potential interactions between the differentially expressed miRNAs and genes using DIANA - miRPath v3.0, a web-based computational tool.
Results/Discussion: Forty-seven out of the 740 genes were differentially expressed between the metastatic and non-metastatic lesions. Considering only these differentially expressed genes, the clustering analysis divided all the cases into two distinct groups: one included mainly the metastatic cases (82%), and the other one the majority of non-metastatic FVPTCs (75%). Additionally, 35 out of the 798 miRNAs were differentially expressed between the two groups, and the clustering analysis performed using these 35 miRNAs generated two main clusters. The first one included 9 metastatic FVPTCs only, whereas the second one included all the non-metastatic tumors and two metastatic FVPTCs.
In addition, the 47 genes and 35miRNAs differentially expressed between Met and NonMet lesions were used to study the potential interactions miRNA-mRNA using DIANA-miRPath v3.0.
We identified 34 enriched pathways. Three out of the 34enriched pathways, the ECM-receptor interaction (hsa04512), the TGF-β signaling (hsa04350) and the Cell Cycle (hsa04110) and pathways, were included in the PanCancer Progression Panel. In 2 out of 3 pathways, some miRNAs targeted genes differentially expressed between the two groups, determining an interaction miRNA-mRNA.
Conclusions: Our results clearly indicate that FVPTCs with metastatic abilities have different gene and miRNA expression profiles compared to their non-metastatic counterparts. A prospective validation is needed to evaluate the usefulness of this molecular approach in the early identification of high-risk FVPTCs.
Aim: Firstly, the primary goal of this study was to investigate the gene and miRNA expression profiles in two groups of homogeneous FVPTCs that were distinguished only by the presence of distant metastasis. The ultimate goal, however, would be to include these expression profiles in a larger project and use them as useful tools to detect precociously those carcinomas with extremely aggressiveness and metastatic behavior.
Methods/Case Presentation: Twelve primary FVPTCs with distant metastasis and 12 non-metastatic FVPTCs with similar clinicopathological features were selected. All tumors were analyzed with the nanoString nCounter system for gene and miRNA expression using two distinct panels, composed of 740 genes, involved in cancer progression, and 798 miRNAs, respectively. Expression data were analyzed using the nanoString nSolver 3.0 software, and an unsupervised hierarchical clustering analysis was performed. In addition, we performed the analysis to evaluate the potential interactions between the differentially expressed miRNAs and genes using DIANA - miRPath v3.0, a web-based computational tool.
Results/Discussion: Forty-seven out of the 740 genes were differentially expressed between the metastatic and non-metastatic lesions. Considering only these differentially expressed genes, the clustering analysis divided all the cases into two distinct groups: one included mainly the metastatic cases (82%), and the other one the majority of non-metastatic FVPTCs (75%). Additionally, 35 out of the 798 miRNAs were differentially expressed between the two groups, and the clustering analysis performed using these 35 miRNAs generated two main clusters. The first one included 9 metastatic FVPTCs only, whereas the second one included all the non-metastatic tumors and two metastatic FVPTCs.
In addition, the 47 genes and 35miRNAs differentially expressed between Met and NonMet lesions were used to study the potential interactions miRNA-mRNA using DIANA-miRPath v3.0.
We identified 34 enriched pathways. Three out of the 34enriched pathways, the ECM-receptor interaction (hsa04512), the TGF-β signaling (hsa04350) and the Cell Cycle (hsa04110) and pathways, were included in the PanCancer Progression Panel. In 2 out of 3 pathways, some miRNAs targeted genes differentially expressed between the two groups, determining an interaction miRNA-mRNA.
Conclusions: Our results clearly indicate that FVPTCs with metastatic abilities have different gene and miRNA expression profiles compared to their non-metastatic counterparts. A prospective validation is needed to evaluate the usefulness of this molecular approach in the early identification of high-risk FVPTCs.
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